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Over many decades the biological surfaces of aquatic swimmers have been studied for their potential as drag reducing surfaces. The hydrodynamic benefit of riblets, or grooves embedded parallel to the flow which appear on surfaces such as shark skin, have been well documented. However the skin of dolphins is embedded with sinusoidal grooves that run perpendicular or transverse to the flow over their bodies. It is theorized that the transverse grooves present on dolphin skin trap vortices between them, creating a partial slip condition over the surface and inducing turbulence augmentation in the boundary layer, thus acting as a potential mechanism to reduce flow separation and thus pressure drag. In an attempt to test this hypothesis and study these effects, an adverse pressure gradient was induced above a flat plate resulting in a controlled region of flow separation occurring within a tripped, turbulent boundary layer. Small transverse grooves of both rectangular and sinusoidal shape were 3D printed and mounted to the plate to measure their effect on the boundary layer flow. The results were compared to a flat plate without grooves using digital particle image velocimetry (DPIV). The strength of the adverse pressure gradient was varied, and the observed control in flow separation and other effects upon the boundary layer are discussed.

The application of frequency adaptive anti-roll tanks on fishing vessels is well established but currently restricted to U-tube designs. This paper concerns the initial stages of a research programme to develop a more generic anti-roll system that will be applicable to a range of tank geometries, with minimal alteration to the existing tank structure. Two possible control strategies, based on continuous and intermittent fluid flow, are assessed for a U-tube tank and the potential of extending the technique to a free-surface tank with a central partition is examined. The intermittent flow scheme was found to be most effective at longer roll periods while the continuous flow scheme was heavily reliant on a low value of fluid flow resistance.

The use of self-organizing fuzzy logic controllers (SOFLCs) in high-speed multi-variable systems has been largely limited by the high number of rules generated, and by the application specific nature of the learning process. This paper concerns the development of a more generically applicable form of an SOFLC that uses a limited rule base of predetermined size, resulting in improved generalization properties and a reduction in the processing time. A simulation study on a four-valve water hydraulic actuator for a subsea robotic arm shows how this method can be applied to system modelling, the resulting 48-rule fuzzy model then providing the necessary process model for training the SOFLC. Using this fuzzy model the SOFLC was able to tune a set of 12 rules to control the actuator and then to adapt these rules to compensate for a simulated leak of hydraulic fluid.

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